Cloudcommuting: Rethinking P2P Urban Mobility Systems

Term: Fall 2014, Wednesdays 12:10 p.m. to 3:00 p.m.
Instructor: Dimitris Papanikolaou – dpap@nyu.edu
Office Hours: Wednesdays after class (3:15-6 pm)


This course introduces the theory, underlying technologies, and operational complexities of intelligent mobility on demand (MoD) systems, using NYC Citi Bike sharing program as a living laboratory. MoD systems utilize networks of parking stations and shared fleets of vehicles (bikes, scooters, automobiles) allowing users to make point-to-point trips on demand. Today, more than 800 bike sharing systems around the world mobilize 3 million trips every day while at least 200 additional systems are planned. Despite their convenience and advanced technology, asymmetric trip patterns cause many stations to temporarily deplete from bikes while others from parking spaces decreasing reliability and level of service in the system. Operators today spend their entire usage revenues paying gas, trucks, and workers to manually move bikes from full to empty stations. Yet, level of service is often low. In Paris 48% of users find no bikes and 58% of users find no parking spaces available. In Barcelona, 50% of the stations are either empty or full during 30% of the time. In this course we will study the limits of efficiency of existing operation models and explore how information technology, social mechanism design, and game theory can be used to design the next generation of intelligent self-organizing MoD systems that motivate their own users to rebalance the fleet instead of trucks and employees.

This course is interdisciplinary. We will cover topics on information and communication technology, data visualization, systems theory, game theory, behavioral economics and mechanism design, ecology, and interaction design. You are expected to be highly motivated and find resources online on your own. We will not have the time to cover in depth all topics, tools and resources in class. By the end of the course our goal is to get a overview of the state of the art in urban intelligence and a basic understanding of how intelligent MoD systems can be designed, engineered and operated, both from technical and economic aspects.


Structure & Work

The course is structured in two parts and combines lectures, talks, discussions, and technical skill workshops. The first part (weeks 1-5) studies the current operational and economic limitations of MoD systems from a systems theory perspective with a focus on bike sharing. Working with data visualization (Processing or D3 programming languages) and advanced computer simulation methods (system dynamics and/or multi-agent models) we will explore how user trip patterns and truck repositioning methods affect system performance during economic equilibrium (e.g. ridership revenues cover operation costs) using NYC Citi Bike as a case study. The second part of the course (weeks 5-12) explores new models of collective intelligence for the next generation of self-organizing MoD systems using digital media and social computation. You will learn how information technology, social mechanism design and game theory can leverage crowd-sourced self-organization in MoD systems by designing, prototyping, and playing an interactive game experiment.

The work consists of weekly readings and assignments, two projects, and a position paper.

Weekly assignments

All weekly assignments are due the beginning of next class. You are expected to post your responses on the weekly assignments on the course blog and be ready to discuss them at the beginning of each class. For the two projects you may either work individually or in teams (preferably) depending on the size and scope of your project and on how clearly you will divide tasks and responsibilities among your teammates.

Mid Term project (due week 5)

For the mid-term project you will work in teams to analyze NYC Citi Bike as a P2P urban resource allocation system working with both data visualization and computer simulation models. You can use Citi Bike’s System Data or live data feed or other information or data sources you may find online. Think of bikes, docks, users, trucks, and energy or cost. For example you may create a simulation model to explain or replicate a pattern you observed in the data. Or, you may come up a performance metric based on which you will try to assess how Citi Bike rebalances its fleet or how well it serves its user demand. For example how much demand does Citi Bike currently serve and how much is the maximum demand it can serve? During mid-term reviews, you will present your analysis of NYC Citi Bike.

Final project (due week 12)

For the final project you will design, prototype, and play an experimental game that integrates physical, digital, and social domains to explore how incentive mechanisms and opportunistic selfish behavior create a bottom-up approach to govern MoD systems. You may either design an interactive installation inside ITP building or use CitiBike to develop a strategy using mobile phones. Be mindful that we will not have the time to cover all technical aspects of those directions so the choice will depend on your skills. In any case the focus will be on closing the loop between sensing, incentivizing, informing, and acting instead of the chosen underlying technology. Possible directions for final projects include (but not limited to):

  • An interactive strategic game experiment-installation inside ITP building. For this option, you will design and prototype an interactive strategic game/installation using sensors, Arduino microcontrollers, wired/wireless communication networks, and interaction design, to study decision-making of players and equilibrium of the game.
  • An urban-scale game experiment using NYC Citi Bike as a living laboratory and mobile devices. For this option, you will design and conduct a controlled urban life experiment using mobile devices and the Internet to test how incentives, time constraints, and substitute transportation options in NYC, affect decision-making of participants.
  • An online participatory simulation game.
  • A navigation/visualization interface for users of Citi Bike that influences behavior

Position paper (due week 12)

In either direction, you must use your final project in combination with a position paper to address a research question ideally in relation to the study you will conduct in the first part of the course.



You will be building in teams an interactive system consisting of Arduinos, RFID sensors, or other means of interaction. The cost of your project will depend on your decisions and the technical means you will choose.


You are expected to document your progress in the class’s blog and participate in the discussions. Make sure you cite the sources of your code, ideas, inspirations and techniques. Other people must be able to read your posts and find your resources.

Textbook & Online resources

There is no required textbook – a list of individual readings and links is provided in the syllabus. Additional readings and links to online resources will be provided before each class if needed.

Office Hours

By appointment, Wednesdays after class, 3pm-6pm. I will also be responding to emails Sundays-Wednesdays.


  • Class participation 40%
  • Weekly assignments 10%
  • Mid-term project 10%
  • Final project 30%
  • Position paper 10%

Guest Speakers & Reviewers

October 1st, Evangelos Kotsioris, PhD Candidate, School of Architecture, Princeton University

October 29th: Justin Cranshaw, PhD Candidate in Computer Science, Carnegie Mellon University

November 5th: Michael Pellegrino, the Director of Operations at NYC CitiBike

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